Integrative Analysis of Metabolomic and Transcriptomic Data Reveals Metabolic Alterations in Glioma Patients.
Yingying ShiDaling DingLiwei LiuZhuolun LiLihua ZuoLin ZhouQiuzheng DuZiwei JingXiaojian ZhangZhi SunPublished in: Journal of proteome research (2021)
Glioma is a malignant brain tumor. There is growing evidence that its progression involves altered metabolism. This study's objective was to understand how those metabolic perturbations were manifested in plasma and urine. Metabolic signatures in blood and urine were characterized by liquid chromatography-tandem mass spectrometry. The results were linked to gene expression using data from the Gene Expression Omnibus database. Genes and pathways associated with the disease were thus identified. Forty metabolites were identified, which were differentially expressed in the plasma of glioma patients, and 61 were identified in their urine. Twenty-two metabolites and five disturbed pathways were found both in plasma and urine. Twelve metabolites in plasma and three in urine exhibited good diagnostic potential for glioma. Transcriptomic analyses revealed specific changes in the expression of 1437 genes associated with glioma. Seventeen differentially expressed genes were found to be correlated with four of the metabolites. Enrichment analysis indicated that dysregulation of glutamatergic synapse pathway might affect the pathology of glioma. Integration of metabolomics with transcriptomics can provide both a broad picture of novel cancer signatures and preliminary information about the molecular perturbations underlying glioma. These results may suggest promising targets for developing effective therapies.
Keyphrases
- gene expression
- ms ms
- end stage renal disease
- liquid chromatography tandem mass spectrometry
- genome wide
- single cell
- ejection fraction
- dna methylation
- newly diagnosed
- chronic kidney disease
- peritoneal dialysis
- prognostic factors
- squamous cell carcinoma
- patient reported outcomes
- electronic health record
- healthcare
- simultaneous determination
- big data
- mass spectrometry
- social media
- long non coding rna
- single molecule
- data analysis
- genome wide identification
- liquid chromatography